Differential arousal regulation by prokineticin 2 signaling in the nocturnal mouse and the diurnal monkey

The temporal organization of activity/rest or sleep/wake rhythms for mammals is regulated by the interaction of light/dark cycle and circadian clocks. The neural and molecular mechanisms that confine the active phase to either day or night period for the diurnal and the nocturnal mammals are unclear. Here we report that prokineticin 2, previously shown as a circadian clock output molecule, is expressed in the intrinsically photosensitive retinal ganglion cells, and the expression of prokineticin 2 in the intrinsically photosensitive retinal ganglion cells is oscillatory in a clock-dependent manner. We further show that the prokineticin 2 signaling is required for the activity and arousal suppression by light in the mouse. Between the nocturnal mouse and the diurnal monkey, a signaling receptor for prokineticin 2 is differentially expressed in the retinorecipient suprachiasmatic nucleus and the superior colliculus, brain projection targets of the intrinsically photosensitive retinal ganglion cells. Blockade with a selective antagonist reveals the respectively inhibitory and stimulatory effect of prokineticin 2 signaling on the arousal levels for the nocturnal mouse and the diurnal monkey. Thus, the mammalian diurnality or nocturnality is likely determined by the differential signaling of prokineticin 2 from the intrinsically photosensitive retinal ganglion cells onto their retinorecipient brain targets

Monitoring the effectiveness of fatigue risk management : A survey of pilots' concerns

INTRODUCTION: Airlines are required to monitor the effectiveness of their pilot fatigue risk management. The present survey sought the views of all pilots at Delta Air Lines on fatigue-related issues raised by their colleagues participating in regular airline safety audits. METHODS: All 13,217 pilots from 9 aircraft fleets were invited to participate in an anonymous online survey. Questions related to aspects of scheduling, fatigue mitigations, and fatigue safety culture. RESULTS: There were 1108 pilots who completed the survey (response rate = 8.4%). On 7/9 fleets, most pilots thought 5- to 7-d rotations were too long (exceptions: B747, median = 14 d; A330 median = 8.5 d). In the previous year, on average across all fleets, 60.6% of pilots had worked up to or beyond their personal rotation limit (minimum, B747 = 6.3%; maximum, MD88/90 = 75.9%). Rotations where duty periods start progressively earlier were considered highly fatiguing by 73.8% of pilots, compared to 14.7% for rotations where duty periods started progressively later and 1.6% for rotations with successive duty periods starting at the same time. The median optimum break length between rotations was 3-4 d. On 7/9 fleets, fewer than 20% of pilots tried to build their monthly schedules with back-to-back rotations (exceptions: B747, 43.8%; A330, 34.3%). Awareness of fatigue and perceptions of company fatigue risk management activities varied widely among fleets. DISCUSSION: The findings identify possible improvements in fatigue risk management and highlight that care is needed when extrapolating from one operational context to another. As a safety assurance exercise, we recommend repeating the survey biannually, or sooner if warranted by specific circumstances.</p

Development and evaluation of a matrix for assessing fatigue-related risk, derived from a national survey of nurses' work patterns

Background: Multiple aspects of nurses’ rosters interact to affect the quality of patient care they can provide and their own health, safety and wellbeing. Objectives: (1) Develop and test a matrix incorporating multiple aspects of rosters and recovery sleep that are individually associated with three fatigue-related outcomes - fatigue-related clinical errors, excessive sleepiness and sleepy driving; and (2) evaluate whether the matrix also predicts nurses’ ratings of the effects of rosters on aspects of life outside work. Design: Develop and test the matrix using data from a national survey of nurses’ fatigue and work patterns in six hospital-based practice areas with high fatigue risk. Methods: Survey data included demographics, work patterns (previous 14 days), choice about shifts, and the extent to which work patterns cause problems with social life, home life, personal relationships, and other commitments (rated 1 = not at all to 5 = very much). Matrix variables were selected based on univariate associations with the fatigue-related outcomes, limits in the collective employment contract, and previous research. Each variable was categorised as lower (score 0), significant (score 1), or higher risk (score 2). Logistic multiple regression modelling tested the independent predictive power of matrix scores against models including all the (uncategorised) work pattern and recovery sleep variables with significant univariate associations with each outcome variable. Model fit was measured using Akaike and Bayesian Information Criterion statistics. Results: Data were included from 2358 nurses who averaged at least 30 h/week in the previous fortnight in one of the target practice areas. Final matrix variables were: total hours worked; number of shift extensions >30 min, night shifts; breaks < 9 h; breaks ≥ 24 h; nights with sleep 11pm to 7am; days waking fully rested; and roster change. After controlling for gender, ethnicity, years of nursing experience, and the extent of shift choice, the matrix score was a significant independent predictor of each of the three fatigue-related outcomes, and for all four aspects of life outside work. For all outcome variables, the model including the matrix score was a better fit to the data than the equivalent model including all the (uncategorised) work pattern variables. Conclusions: A matrix that predicts the likelihood of nurses reporting fatigue-related safety outcomes can be used to compare the impact of rosters both at work and outside work. It can be used for roster design and management, and to guide nurses’ choices about the shifts they work.</p

Fatigue and nurses’ work patterns : An online questionnaire survey

Background: Fatigue resulting from shift work and extended hours can compromise patient care and the safety and health of nurses, as well as increasing nursing turnover and health care costs. Objectives: This research aimed to identify aspects of nurses’ work patterns associated with increased risk of reporting fatigue-related outcomes. Design: A national survey of work patterns and fatigue-related outcomes in 6 practice areas expected to have high fatigue risk (child health including neonatology, cardiac care/intensive care, emergency and trauma, in-patient mental health, medical, and surgical nursing). Methods: The 5-page online questionnaire included questions addressing: demographics, usual work patterns, work in the previous two weeks, choice about shifts, and four fatigue-related outcomes – having a sleep problem for at least 6 months, sleepiness (Epworth Sleepiness Scale), recalling a fatigue-related error in clinical practice in the last 6 months, and feeling close to falling asleep at the wheel in the last 12 months. The target population was all registered and enrolled nurses employed to work in public hospitals at least 30 h/week in one of the 6 practice areas. Participation was voluntary and anonymous. Results: Respondents (n = 3133) were 89.8% women and 8% Māori (indigenous New Zealanders), median age 40 years, range 21–71 years (response rate 42.6%). Nurses were more likely than New Zealand adults in general to report chronic sleep problems (37.73%vs 25.09%, p < 0.0001) and excessive sleepiness (33.75% vs 14.9%, p < 0.0001). Fatigue-related error(s) in the last 6 months were recalled by 30.8% and 64.50% reported having felt sleepy at the wheel in the last 12 months. Logistic regression analyses indicated that fatigue-related outcomes were most consistently associated with shift timing and sleep. Risk increased with more night shifts and decreased with more nights with sleep between 11 p.m. and 7 a.m. and on which nurses had enough sleep to feel fully rested. Risk also increased with roster changes and more shift extensions greater than 30 min and decreased with more choice about shifts. Comparisons between intensive care/cardiac care and in-patient mental health nursing highlight that fatigue has different causes and consequences in different practice areas. Conclusions: Findings confirm the need for a more comprehensive and adaptable approach to managing fatigue. We advocate an approach that integrates safety management and scientific principles with nursing and management expertise. It should be data-driven, risk-focused, adaptable, and resilient in the face of changes in the services required, the resources available, and the overall goals of the healthcare system.</p

IPO: a tool for automated optimization of XCMS parameters

BACKGROUND: Untargeted metabolomics generates a huge amount of data. Software packages for automated data processing are crucial to successfully process these data. A variety of such software packages exist, but the outcome of data processing strongly depends on algorithm parameter settings. If they are not carefully chosen, suboptimal parameter settings can easily lead to biased results. Therefore, parameter settings also require optimization. Several parameter optimization approaches have already been proposed, but a software package for parameter optimization which is free of intricate experimental labeling steps, fast and widely applicable is still missing. RESULTS: We implemented the software package IPO (‘Isotopologue Parameter Optimization’) which is fast and free of labeling steps, and applicable to data from different kinds of samples and data from different methods of liquid chromatography - high resolution mass spectrometry and data from different instruments.IPO optimizes XCMS peak picking parameters by using natural, stable 13C isotopic peaks to calculate a peak picking score. Retention time correction is optimized by minimizing relative retention time differences within peak groups. Grouping parameters are optimized by maximizing the number of peak groups that show one peak from each injection of a pooled sample. The different parameter settings are achieved by design of experiments, and the resulting scores are evaluated using response surface models. IPO was tested on three different data sets, each consisting of a training set and test set. IPO resulted in an increase of reliable groups (146% - 361%), a decrease of non-reliable groups (3% - 8%) and a decrease of the retention time deviation to one third. CONCLUSIONS: IPO was successfully applied to data derived from liquid chromatography coupled to high resolution mass spectrometry from three studies with different sample types and different chromatographic methods and devices. We were also able to show the potential of IPO to increase the reliability of metabolomics data.The source code is implemented in R, tested on Linux and Windows and it is freely available for download at https://github.com/glibiseller/IPO. The training sets and test sets can be downloaded from https://health.joanneum.at/IPO

An Untargeted Metabolomics Approach to Characterize Short-Term and Long-Term Metabolic Changes after Bariatric Surgery

<div><p>Bariatric surgery is currently one of the most effective treatments for obesity and leads to significant weight reduction, improved cardiovascular risk factors and overall survival in treated patients. To date, most studies focused on short-term effects of bariatric surgery on the metabolic profile and found high variation in the individual responses to surgery. The aim of this study was to identify relevant metabolic changes not only shortly after bariatric surgery (Roux-en-Y gastric bypass) but also up to one year after the intervention by using untargeted metabolomics. 132 serum samples taken from 44 patients before surgery, after hospital discharge (1–3 weeks after surgery) and at a 1-year follow-up during a prospective study (NCT01271062) performed at two study centers (Austria and Switzerland). The samples included 24 patients with type 2 diabetes at baseline, thereof 9 with diabetes remission after one year. The samples were analyzed by using liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS, HILIC-QExactive). Raw data was processed with XCMS and drift-corrected through quantile regression based on quality controls. 177 relevant metabolic features were selected through Random Forests and univariate testing and 36 metabolites were identified. Identified metabolites included trimethylamine-<i>N</i>-oxide, alanine, phenylalanine and indoxyl-sulfate which are known markers for cardiovascular risk. In addition we found a significant decrease in alanine after one year in the group of patients with diabetes remission relative to non-remission. Our analysis highlights the importance of assessing multiple points in time in subjects undergoing bariatric surgery to enable the identification of biomarkers for treatment response, cardiovascular benefit and diabetes remission. Key-findings include different trend pattern over time for various metabolites and demonstrated that short term changes should not necessarily be used to identify important long term effects of bariatric surgery.</p></div

Clinical characteristics of study population, presented in mean (± SD) for each sampling point: PRE (before surgery), POST (1–2 weeks after surgery), FU (one year after surgery) including p-values from paired t-tests.

<p>Clinical characteristics of study population, presented in mean (± SD) for each sampling point: PRE (before surgery), POST (1–2 weeks after surgery), FU (one year after surgery) including p-values from paired t-tests.</p